According to estimates in 2008 by the Centers for Disease Control and Prevention (CDC), nearly 24 million Americans have been diagnosed with obesity-induced Type II Diabetes Mellitus (T2D) (CDC2008). Treatments are currently available for T2D. However, there continues to be an increase in the number of diagnosed individuals each year, which might lead one to conclude that current treatments are not entirely effective. One of the leading treatments for T2D is oral administration of drugs in the thiazolidinedione compound group. The most widely used member of this group, rosiglitazone, is found in drugs like Avandia(R) (GlaxoSmithKline), for which adverse side effects are observed with use. Many patients experience swelling or water weight gain, and present symptoms placing them at higher risk for heart attacks (1, 2). Thiazolidinediones (TZDs) work by targeting peroxisome proliferator-activated receptor-gamma (PPAR(), which is a protein known to play a key role in regulation of inflammation and metabolic processes, cancers, and vascular function (3). Despite the side effects seen with current treatment options, changing the target does not seem like the correct choice because TZD-induced activity does correct the insulin resistance and chronic inflammation problem seen in individuals with T2D. Instead, a change in the products that are used to treat T2D and other chronic inflammation-related diseases, such as inflammatory bowel disease and atherosclerosis, is the best course of action. Therefore, we propose focusing drug discovery and design techniques on mining for natural compounds that bind to PPAR(. Fatty acids and derivatives of these compounds have been suggested as the endogenous ligand for PPARs (4-6). Ideally, finding a fatty acid or similar biological compound that is abundant in nature and can activate PPAR( may be the best candidate for drug development and treatment of T2D. However, the number of potential natural compounds that could activate PPAR( and/or the other subtypes (PPARa and PPARd) is too large for a compound-by-compound analysis. A time- and cost-effective method for searching through these compounds is necessary. To this end, we have initiated a collaborative project between our computational molecular modeling laboratory and the Nutritional Immunology and Molecular Medicine Group at Virginia Tech to develop and test a virtual screening process. One aspect of this study will involve a detailed analysis of PPARa, -d, and -( to extrapolate information pertaining to this protein family that may influence ligand binding. In addition, molecular docking-based virtual screening with a human PPAR( model will be used in conjunction with experimental validation using ligand-binding assays, PPAR( reporter activity assays, and T2D-specific mouse models of PPAR( deficiency.